Market intelligence and automated trading in one app
Institutional-grade prediction market data, arbitrage intelligence, and cross-venue order book normalization
Stage
MVP
Not given
Founded
2026
Not given
Based in
FR
Not given
Pricing model
Free trial
Not given
Pricing
2 days free, no card. Then a 14-day trial, then €39/month. Trading add-on €19/month plus €0.03 per executed order. Developer API: €2 free credit to start, then €0.002 per call, top-ups from €20.
Hobbyist: Free ($0/month) with 30 req/min rate limit and 24h lookback. Quant Pro: $30/month (billed monthly) or $24/month (billed annually, save 20%) with 180 req/min, 90-day archives, and 1M rows/day export. Institutional: $100/month (billed monthly) or $80/month (billed annually, save 20%) with 60
Key features
Monitor 600+ crypto markets with minute-by-minute price refreshes
Alerts ranked CRITICAL, HIGH and WATCH
Market states: strengthening, weakening, emerging, returning to normal
Personal watchlist for markets you care about
Market breadth view
Automated and manual trading on Kraken, OKX or Coinbase
Stop-loss on every entry and order caps
Developer API with access to 600+ crypto tickers and FX rates
WordPress plugin and browser extension (Market Radar)
Millisecond L2 reconstruction with dual timestamping
Settlement fungibility scoring (0–100)
Cross-venue canonical pair matching and symbology
Real-time WebSocket feeds and REST API endpoints
Event-driven backtesting engine with latency modeling
Python and TypeScript SDKs
Parquet tick archive downloads
Market metadata and settlement provenance catalog
What makes it different
Focused alerts ranked by importance instead of notification noise
Trade on your own exchange account without Waveleta holding funds
Alerts checked every 60 seconds and delivered within seconds
Clear market state descriptions instead of technical jargon
Covers seven prediction market venues in a single normalized API
Quantifies settlement risk with 0–100 fungibility scoring on oracle divergence and cutoff mismatches
Eliminates backfill problem with continuous millisecond-level historical L2 reconstruction